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    • 1. 发明授权
    • Method of forming a passivation layer of a DRAM
    • 形成DRAM钝化层的方法
    • US06261891B1
    • 2001-07-17
    • US09492669
    • 2000-01-28
    • Tzu-Min ChengChin-Hui Lee
    • Tzu-Min ChengChin-Hui Lee
    • H01L218234
    • H01L21/76897H01L21/02129H01L21/0214H01L21/022H01L21/02271H01L21/02274H01L21/3145H01L21/31625H01L21/76832H01L21/76834H01L27/10888
    • The present invention provides a method of forming a passivation layer of a DRAM on a semiconductor wafer. The semiconductor wafer comprises a silicon substrate, and two adjacent gates positioned on the surface of the silicon substrate wherein each gate comprises a spacer on each of two opposite walls. The method comprises forming a first silicon-oxygen-nitride layer of predetermined thickness on the semiconductor wafer, forming a second silicon-oxygen-nitride layer of predetermined thickness on the first silicon-oxygen-nitride layer and forming a BPSG (borophosphosilicate glass) layer uniformly on the second silicon-oxygen-nitride to planarize the surface of the semiconductor wafer. The BPSG layer is used as a dielectric layer. The first silicon-oxygen-nitride layer serves as diffusion barrier layer to prevent diffusion of boron and phosphorous from the BPSG layer into the silicon substrate. The second silicon-oxygen-nitride layer is used as an etching stop layer. The first and the second silicon-oxygen-nitride layers together constitute the passivation layer of the DRAM. The extinction coefficient of the first layer is smaller than that of the second layer, and the extinction coefficient of the first and the second layers is between 0.3 and 0.8.
    • 本发明提供了在半导体晶片上形成DRAM的钝化层的方法。 半导体晶片包括硅衬底和位于硅衬底的表面上的两个相邻栅极,其中每个栅极包括在两个相对的壁中的每一个上的间隔物。 该方法包括在半导体晶片上形成预定厚度的第一硅 - 氮化氮层,在第一硅 - 氮 - 氮化物层上形成预定厚度的第二硅 - 氮 - 氮化物层,并形成BPSG(硼磷硅酸盐玻璃)层 在第二硅 - 氮化硅上均匀地平坦化半导体晶片的表面。 BPSG层用作电介质层。 第一硅 - 氮化氮层用作扩散阻挡层,以防止硼和磷从BPSG层扩散到硅衬底中。 第二硅 - 氮化氮层用作蚀刻停止层。 第一和第二硅 - 氮化氮层一起构成DRAM的钝化层。 第一层的消光系数小于第二层的消光系数,第一层和第二层的消光系数在0.3和0.8之间。
    • 2. 发明授权
    • Method of forming a level silicon oxide layer on two regions of different heights on a semiconductor wafer
    • 在半导体晶片上在不同高度的两个区域上形成层状氧化硅层的方法
    • US06235354B1
    • 2001-05-22
    • US09431940
    • 1999-11-01
    • Chin-Hui LeeTing-Chi LinChih-Cheng Liu
    • Chin-Hui LeeTing-Chi LinChih-Cheng Liu
    • H01L21306
    • H01L21/02164H01L21/02271H01L21/02307H01L21/31051H01L21/31612
    • The present invention relates to a method of forming a level silicon oxide layer on a semiconductor wafer. The semiconductor wafer comprises a substrate having a first region containing no silicon nitride on its surface and a second region which is higher than the first region and contains a silicon nitride layer on its surface. The method comprises performing a cleaning process on the semiconductor wafer with an alkaline solution to uniform the deposition rate over the surface of the first region; and performing a deposition process employing ozone as a reactive gas with a flow capacity of 80-200 g/L to form a silicon oxide layer above the first and second regions wherein the deposition rate of the silicon oxide layer on the first region is higher than that on the second region and the silicon oxide layer above the first region is leveled with that above the second region after a predetermined period of time.
    • 本发明涉及在半导体晶片上形成层状氧化硅层的方法。 半导体晶片包括具有在其表面上不含氮化硅的第一区域和高于第一区域的第二区域并且在其表面上包含氮化硅层的衬底。 该方法包括用碱性溶液对半导体晶片进行清洁处理以使在第一区域的表面上的沉积速率均匀; 并且使用臭氧作为流动能力为80-200g / L的反应气体进行沉积工艺,以在第一和第二区域上方形成氧化硅层,其中第一区域上的氧化硅层的沉积速率高于 在第一区域上方的第二区域和氧化硅层在预定时间段之后与第二区域上方的氧化硅层平齐。
    • 4. 发明授权
    • Technique for adaptation of hidden markov models for speech recognition
    • 用于语音识别的隐马尔可夫模型的适应技术
    • US6151574A
    • 2000-11-21
    • US149782
    • 1998-09-08
    • Chin-Hui LeeKoichi Shinoda
    • Chin-Hui LeeKoichi Shinoda
    • G10L15/06G10L15/14
    • G10L15/065G10L15/144
    • A speech recognition system learns characteristics of speech by a user during a learning phase to improve its performance. Adaptation data derived from the user's speech and its recognized result is collected during the learning phase. Parameters characterizing hidden Markov Models (HMMs) used in the system for speech recognition are modified based on the adaptation data. To that end, a hierarchical structure is defined in an HMM parameter space. This structure may assume the form of a tree structure having multiple layers, each of which includes one or more nodes. Each node on each layer is connected to at least one node on another layer. The nodes on the lowest layer of the tree structure are referred to as "leaf nodes." Each node in the tree structure represents a subset of the HMM parameters, and is associated with a probability measure which is derived from the adaptation data. In particular, each leaf node represents a different one of the HMM parameters, which is derivable from the probability measure associated with the leaf node. This probability measure is a function of the probability measures which are associated with the nodes connected to the leaf node, and which represent "hierarchical priors" to such a probability measure.
    • 语音识别系统在学习阶段学习用户的语音特征,以提高其性能。 在学习阶段收集从用户言语导出的适应数据及其识别结果。 基于自适应数据修改表征用于语音识别的系统中的隐马尔可夫模型(HMM)的参数。 为此,在HMM参数空间中定义了层次结构。 该结构可以采用具有多个层的树结构的形式,每个层包括一个或多个节点。 每个层上的每个节点都连接到另一个层上的至少一个节点。 树结构最底层的节点称为“叶节点”。 树结构中的每个节点表示HMM参数的子集,并且与从适配数据导出的概率测量相关联。 特别地,每个叶节点表示HMM参数中的不同的一个,其可以从与叶节点相关联的概率度量导出。 该概率测度是与连接到叶节点的节点相关联的概率测度的函数,并且表示这种概率测量的“分级先验”。
    • 5. 发明授权
    • Method of key-phase detection and verification for flexible speech
understanding
    • 灵活语音理解的关键相位检测和验证方法
    • US5797123A
    • 1998-08-18
    • US771732
    • 1996-12-20
    • Wu ChouBiing-Hwang JuangTatsuya KawaharaChin-Hui Lee
    • Wu ChouBiing-Hwang JuangTatsuya KawaharaChin-Hui Lee
    • G10L15/10G10L15/00G10L15/08G10L15/18G10L15/28G10L9/00
    • G10L15/18G10L15/1815G10L2015/088
    • A key-phrase detection and verification method that can be advantageously used to realize understanding of flexible (i.e., unconstrained) speech. A "multiple pass" procedure is applied to a spoken utterance comprising a sequence of words (i.e., a "sentence"). First, a plurality of key-phrases are detected (i.e., recognized) based on a set of phrase sub-grammars which may, for example, be specific to the state of the dialogue. These key-phrases are then verified by assigning confidence measures thereto and comparing these confidence measures to a threshold, resulting in a set of verified key-phrase candidates. Next, the verified key-phrase candidates are connected into sentence hypotheses based upon the confidence measures and predetermined (e.g., task-specific) semantic information. And, finally, one or more of these sentence hypotheses are verified to produce a verified sentence hypothesis and, from that, a resultant understanding of the spoken utterance.
    • 可以有利地用于实现对柔性(即,无约束)语音的理解的密钥短语检测和验证方法。 对包括一系列单词(即“句子”)的语音话语应用“多重通行证”程序。 首先,基于短语子语法的集合来检测(即,识别)多个关键短语,其可以例如特定于对话状态。 然后通过分配置信度来验证这些密钥短语,并将这些置信度量度与阈值进行比较,得到一组已验证的密钥短语候选。 接下来,基于置信度度量和预定(例如,任务特定)语义信息将经验证的关键词候选者连接成句子假设。 最后,验证这些句子假说中的一个或多个,以产生一个经过验证的句子假设,从而得到对口头发音的理解。
    • 6. 发明授权
    • Speech recognition training method
    • 语音识别训练方法
    • US4718088A
    • 1988-01-05
    • US593891
    • 1984-03-27
    • James K. BakerJohn W. KlovstadChin-Hui LeeKalyan Ganesan
    • James K. BakerJohn W. KlovstadChin-Hui LeeKalyan Ganesan
    • G10L11/02G10L15/02G10L15/06G10L15/08G10L15/12G10L5/00
    • G10L25/87G10L15/063G10L15/083G10L15/02G10L15/12G10L2015/0638G10L25/27
    • A speech recognition method and apparatus employ a speech processing circuitry for repetitively deriving from a speech input, at a frame repetition rate, a plurality of acoustic parameters. The acoustic parameters represent the speech input signal for a frame time. A plurality of template matching and cost processing circuitries are connected to a system bus, along with the speech processing circuitry, for determining, or identifying, the speech units in the input speech, by comparing the acoustic parameters with stored template patterns. The apparatus can be expanded by adding more template matching and cost processing circuitry to the bus thereby increasing the speech recognition capacity of the apparatus. Template pattern generation is advantageously aided by using a "joker" word to specify the time boundaries of utterances spoken in isolation, by finding the beginning and ending of an utterance surrounded by silence.
    • 语音识别方法和装置采用语音处理电路,以帧重复率重复地从语音输入中导出多个声学参数。 声学参数表示帧时间的语音输入信号。 通过将声学参数与存储的模板图案进行比较,多个模板匹配和成本处理电路连同语音处理电路连接到用于确定或识别输入语音中的语音单元的系统总线。 可以通过向总线添加更多的模板匹配和成本处理电路来扩展该装置,从而增加装置的语音识别能力。 通过使用“小丑”字通过找到由沉默包围的话语的开始和结束来有助于指定孤立地说出的话语的时间边界。
    • 8. 发明授权
    • Method and apparatus using discriminative training in natural language call routing and document retrieval
    • 在自然语言呼叫路由和文档检索中使用区分性训练的方法和装置
    • US06925432B2
    • 2005-08-02
    • US09748433
    • 2000-12-26
    • Chin-Hui LeeHong-Kwang Jeff Kuo
    • Chin-Hui LeeHong-Kwang Jeff Kuo
    • G06F17/30G06K9/62G10L15/18G06F17/27
    • G06F17/30707G06K9/6217G10L15/1822G10L15/183
    • A method and apparatus for performing discriminative training of, for example, call routing training data (or, alternatively, other classification training data) which improves the subsequent classification of a user's natural language based requests. An initial scoring matrix is generated based on the training data and then the scoring matrix is adjusted so as to improve the discrimination between competing classes (e.g., destinations). In accordance with one illustrative embodiment of the present invention a Generalized Probabilistic Descent (GPD) algorithm may be advantageously employed to provide the improved discrimination. More specifically, the present invention provides a method and apparatus comprising steps or means for generating an initial scoring matrix comprising a numerical value for each of a set of n classes in association with each of a set of m features, the initial scoring matrix based on a set of training data and, for each element of said set of training data, based on a subset of said features which are comprised in the natural language text of said element of said set of training data and on one of said classes which has been identified therefor; and based on the initial scoring matrix and the set of training data, generating a discriminatively trained scoring matrix for use by said classification system by adjusting one or more of said numerical values such that a greater degree of discrimination exists between competing ones of said classes when said classification requests are performed, thereby resulting in a reduced classification error rate.
    • 用于执行例如呼叫路由训练数据(或替代地,其他分类训练数据)的辨别性训练的方法和装置,其改进了用户基于自然语言的请求的后续分类。 基于训练数据生成初始评分矩阵,然后调整评分矩阵,以便改善竞争类(例如,目的地)之间的区分。 根据本发明的一个说明性实施例,可以有利地采用广义概率下降(GPD)算法来提供改进的辨别。 更具体地,本发明提供了一种方法和装置,包括用于生成初始评分矩阵的步骤或装置,该初始评分矩阵包括与一组m个特征中的每一个相关联的一组n个类中的每一个的数值,基于 一组训练数据,并且对于所述一组训练数据的每个元素,基于所述特征的子集,所述子集包括在所述训练数据集合的所述元素的自然语言文本中,并且已经被 确定; 并且基于所述初始评分矩阵和所述训练数据集合,通过调整所述数值中的一个或多个来产生用于由所述分类系统使用的鉴别训练的评分矩阵,使得当所述类别中的所述类别之间存在较大程度的歧视时, 所述分类请求被执行,从而导致分类错误率降低。
    • 9. 发明授权
    • Method of ion implantation for adjusting the threshold voltage of MOS transistors
    • 用于调整MOS晶体管的阈值电压的离子注入方法
    • US06221703B1
    • 2001-04-24
    • US09352749
    • 1999-07-14
    • Chih-Cheng LiuChin-Hui Lee
    • Chih-Cheng LiuChin-Hui Lee
    • H10L21339
    • H01L29/1033H01L21/2652
    • The invention relates to an ion implantation method for adjusting the threshold voltage of MOS transistors. The MOS transistor is employed in a DRAM (dynamic random access memory) memory cell in a semiconductor wafer and comprises a substrate, a gate insulating layer positioned on the substrate, and a gate conducting layer with a rectangular-shaped cross section positioned on the gate insulating layer. The method comprises performing an ion implantation process at a predetermined dosage and ion energy to implant dopants through the gate conducting layer and gate insulating layer and deposit the dopants into the superficial portion of the substrate below the gate insulating layer.
    • 本发明涉及用于调整MOS晶体管的阈值电压的离子注入方法。 MOS晶体管用于半导体晶片中的DRAM(动态随机存取存储器)存储单元,并且包括基板,位于基板上的栅极绝缘层和位于栅极上的矩形横截面的栅极导电层 绝缘层。 该方法包括以预定剂量和离子能量进行离子注入工艺以通过栅极导电层和栅极绝缘层注入掺杂剂,并将掺杂剂沉积到栅极绝缘层下方的衬底的表面部分中。
    • 10. 发明授权
    • System and method for performing automated dynamic dialogue generation
    • 执行自动动态对话生成的系统和方法
    • US06418440B1
    • 2002-07-09
    • US09334000
    • 1999-06-15
    • Hong-Kwang Jeff KuoChin-Hui LeeAndrew Nason Pargellis
    • Hong-Kwang Jeff KuoChin-Hui LeeAndrew Nason Pargellis
    • G06F1730
    • G06F17/30654
    • A customized method or algorithm for holding an interactive dialogue session between a (human) user and a machine (hereinafter referred to simply as a “dialogue”) is generated, such that the resulting dialogue advantageously responds to the user's requests and wherein the system's capability (i.e., the dialogue) is automatically modified thereafter based on dynamically changing external databases. Specifically, a computer system acts as a Dialogue Generator agent by creating such a customized dialogue consisting of services that are organized and presented in a form that is a combination of the user's expectations and the system's capabilities. In particular, the system's capabilities advantageously include the information content of database/service providers (such as, for example, a distributed information source such as the World Wide Web or a corporate file system), and the Dialogue Generator advantageously modifies the dialogue periodically in response to this dynamically changing external environment.
    • 生成用于在(人)用户和机器之间保持交互式对话会话(以下简称为“对话”)的定制方法或算法,使得所得到的对话有利地响应于用户的请求,并且其中系统的能力 (即,对话)此后将根据动态变化的外部数据库自动修改。 具体来说,计算机系统作为对话生成器代理,通过创建由服务组成的定制对话,该对话组合和呈现为用户期望和系统功能的组合的形式。 特别地,系统的能力有利地包括数据库/服务提供商(例如,诸如万维网或公司文件系统的分布式信息源)的信息内容,并且对话生成器有利地周期性地修改对话 响应这种动态变化的外部环境。